这两种语言具有相似的特性集。性能上的差异来自Fortran不允许混淆的事实，除非使用了EQUIVALENCE语句。任何有别名的代码都不是有效的Fortran，但是它是由程序员而不是编译器来检测这些错误的。因此，Fortran编译器忽略了可能的内存指针别名，并允许它们生成更有效的代码。看一下C语言中的这个小例子:

void transform (float *output, float const * input, float const * matrix, int *n)
{
    int i;
    for (i=0; i<*n; i++)
    {
        float x = input[i*2+0];
        float y = input[i*2+1];
        output[i*2+0] = matrix[0] * x + matrix[1] * y;
        output[i*2+1] = matrix[2] * x + matrix[3] * y;
    }
}

这个函数在优化后会比Fortran函数运行得慢。为什么如此?如果你在输出数组中写入值，你可能会改变矩阵的值。毕竟，指针可以重叠并指向相同的内存块(包括int指针!)C编译器被迫从内存中重新加载所有计算的四个矩阵值。

在Fortran中，编译器只加载一次矩阵值，并将它们存储在寄存器中。它可以这样做是因为Fortran编译器假定指针/数组在内存中不重叠。

Fortunately, the restrict keyword and strict-aliasing have been introduced to the C99 standard to address this problem. It's well supported in most C++ compilers these days as well. The keyword allows you to give the compiler a hint that the programmer promises that a pointer does not alias with any other pointer. The strict-aliasing means that the programmer promises that pointers of different type will never overlap, for example a double* will not overlap with an int* (with the specific exception that char* and void* can overlap with anything).

If you use them you will get the same speed from C and Fortran. However, the ability to use the restrict keyword only with performance critical functions means that C (and C++) programs are much safer and easier to write. For example, consider the invalid Fortran code: CALL TRANSFORM(A(1, 30), A(2, 31), A(3, 32), 30), which most Fortran compilers will happily compile without any warning but introduces a bug that only shows up on some compilers, on some hardware and with some optimization options.

Fortran速度更快有几个原因。然而，它们的重要性是如此无关紧要，或者可以通过任何方式解决，所以它不应该是重要的。现在使用Fortran的主要原因是维护或扩展遗留应用程序。

PURE and ELEMENTAL keywords on functions. These are functions that have no side effects. This allows optimizations in certain cases where the compiler knows the same function will be called with the same values. Note: GCC implements "pure" as an extension to the language. Other compilers may as well. Inter-module analysis can also perform this optimization but it is difficult. standard set of functions that deal with arrays, not individual elements. Stuff like sin(), log(), sqrt() take arrays instead of scalars. This makes it easier to optimize the routine. Auto-vectorization gives the same benefits in most cases if these functions are inline or builtins Builtin complex type. In theory this could allow the compiler to reorder or eliminate certain instructions in certain cases, but likely you'd see the same benefit with the struct { double re; double im; }; idiom used in C. It makes for faster development though as operators work on complex types in Fortran.

The faster code is not really up to the language, is the compiler so you can see the ms-vb "compiler" that generates bloated, slower and redundant object code that is tied together inside an ".exe", but powerBasic generates too way better code. Object code made by a C and C++ compilers is generated in some phases (at least 2) but by design most Fortran compilers have at least 5 phases including high-level optimizations so by design Fortran will always have the capability to generate highly optimized code. So at the end is the compiler not the language you should ask for, the best compiler i know is the Intel Fortran Compiler because you can get it on LINUX and Windows and you can use VS as the IDE, if you're looking for a cheap tigh compiler you can always relay on OpenWatcom.

更多信息: http://ed-thelen.org/1401Project/1401-IBM-Systems-Journal-FORTRAN.html

I think the key point in favor of Fortran is that it is a language slightly more suited for expressing vector- and array-based math. The pointer analysis issue pointed out above is real in practice, since portable code cannot really assume that you can tell a compiler something. There is ALWAYS an advantage to expression computaitons in a manner closer to how the domain looks. C does not really have arrays at all, if you look closely, just something that kind of behaves like it. Fortran has real arrawys. Which makes it easier to compile for certain types of algorithms especially for parallel machines.

在运行时系统和调用约定等方面，C语言和现代的Fortran非常相似，很难看出有什么不同。注意，这里的C实际上是基础C: c++是一个完全不同的问题，具有非常不同的性能特征。

我还没有听说过Fortan比C快得多，但是可以想象在某些情况下它会更快。关键不在于语言特征的存在，而在于那些(通常)不存在的特征。

一个例子是C指针。C指针几乎到处都在使用，但指针的问题是编译器通常无法判断它们是否指向同一个数组的不同部分。

例如，如果你写了一个strcpy例程，看起来像这样:

strcpy(char *d, const char* s)
{
  while(*d++ = *s++);
}

编译器必须在d和s可能是重叠数组的假设下工作。所以当数组重叠时，它不能执行会产生不同结果的优化。正如您所期望的，这在很大程度上限制了可以执行的优化类型。

[我应该注意到，C99有一个“restrict”关键字，显式地告诉编译器指针不重叠。还要注意，Fortran也有指针，语义不同于C语言，但指针不像C语言那样无处不在。

但是回到C与Fortran的问题上，可以想象，Fortran编译器能够执行一些对于(直接编写的)C程序可能无法实现的优化。所以我不会对这种说法感到太惊讶。不过，我确实希望性能差异不会太大。(~ 5 - 10%)

大多数帖子已经提出了令人信服的论点，所以我只是在另一个方面加上众所周知的2美分。

在处理能力方面，fortran更快或更慢是有其重要性的，但如果用fortran开发一些东西需要5倍多的时间，因为:

it lacks any good library for tasks different from pure number crunching it lack any decent tool for documentation and unit testing it's a language with very low expressivity, skyrocketing the number of lines of code. it has a very poor handling of strings it has an inane amount of issues among different compilers and architectures driving you crazy. it has a very poor IO strategy (READ/WRITE of sequential files. Yes, random access files exist but did you ever see them used?) it does not encourage good development practices, modularization. effective lack of a fully standard, fully compliant opensource compiler (both gfortran and g95 do not support everything) very poor interoperability with C (mangling: one underscore, two underscores, no underscore, in general one underscore but two if there's another underscore. and just let not delve into COMMON blocks...)

那么这个问题就无关紧要了。如果某样东西很慢，大多数时候你无法在给定的限制范围内改进它。如果你想要更快，改变算法。最后，使用电脑的时间很便宜。人类的时间不是。珍惜减少人类时间的选择。如果它增加了使用电脑的时间，无论如何它都是有成本效益的。